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Bloodless Glucose Monitor
Presented by: Nelson WuTeam Members: Cong Zhang and Tom Zhou
Client: Dr. Jeffrey Brooks, D.P.M.
NeedDiabetes mellitus attributed to malfunction of
insulin production, a molecule that regulates blood glucose concentrations within the body
Normal glucose level: 70 to 110 mg/dLBlood glucose spike to 180 mg/dL after meals
Normally brought back down by insulin Stay high for 3 hours for people with diabetes
Finger Prick- The Gold StandardPerforms glucose
oxidation and measures changes in sample
Costs approximately $1000 per year in test strips
Requires puncturing the skin which often results in neuropathy
Patient is only willing to puncture skin so many times per day, limiting effectiveness of monitoring
Specific Design RequirementsDevice does not require implanted parts or physically
puncturing the userDevice gives results in a reasonable time frame (within 1
minute)Device displays blood glucose in standard units (mg
glucose/dL blood)Device warns user on detection of dangerous glucose
levels (>200mg/dL or <70mg/dL)Device is lighter than 20 N and smaller than 200 cm3
Device contains internal power for one month of testing (10 W-hr)
Device is accurate within 10% of the commercially-available methods at least 95% of the time
Design PossibilitiesReverse IontophoresisPhotoacoustic EffectOptical Coherence TomographyMultispectral PolarimetryNear-Infrared SpectroscopyRaman Spectroscopy
Reverse IontophoresisExtracting glucose in
fluid drawn from skin using electrical current
Example: G2 Glucowatch, US patent 20080058627
Causes skin irritationRequires daily “finger-
prick” calibrationDisrupted by sweating
Photoacoustic EffectUse laser pulse to heat
tissueMeasure thermal tissue
expansion and acoustic wave
Calculate fluid viscosity and correlative glucose concentration
Not affected by water itself due to poor response
Fluid viscosity confounded
Multispectral PolarimetryMeasures the
intensity of collected polarized light.
Requires low turbidity (i.e. aqueous humor of the eye)
Unaffected by temperature and pH
Time lag
Optical Coherence TomographyBased on the delay of
backscattered light compared to the light reflected by the reference arm mirror
High resolution two-dimensional images by in-depth and lateral scanning
Twenty minute lag from blood glucose levels
The refractive index of the interstitial fluid increases in response to increase in its glucose concentration
Sensitive to motion artifacts and changes in skin temperature
Near Infrared Spectroscopy
Raman Spectroscopy
Measures elastic scattering of light
Strong Water Spectrum785 nm for 1 mm tissue
penetrationWeak tissue
autofluorescenceLess photodamage
Measures inelastic scattering of light
Weak Water Spectrum785 nm for 1 mm tissue
penetrationWeak tissue
autofluorescenceLess photodamage
Raman Spectroscopy785 nm
incident861 nm
Glucose893 nm
hemoglobin
Invasive:Blood pricking methodReverse Iontophoresis
Indirect:Photoacoustic EffectNon-invasive
Elastic:NIR Spectroscopy
Direct Monitor location: EyeMultispectral Polarimetry
Monitor location: Skin Interstitial Space:Optical Coherence Tomography
Overview
Capillaries
Inelastic:Raman Spectroscopy
Analysis to Choose DesignOption Non-
invasiveAccuracy
Portability
Ease of Use
Cost
Total
Blood Prick 1 5 5 4 3 18
Reverse Iontophoresis
3 3 5 2 3 16
Photoacoustic Effect
5 2 3 2 2 14
Multispectral Polarimetry
5 4 2 1 3 15
Optical Coherence Tomography
5 3 2 3 2 15
NIR 5 3 5 4 3 20
Raman 5 5 5 4 3-4 23
Optical ElementsLaser sourceBeam splittersObjective and focusing lensBandpass filtersPhotodetectors
Non-Optical ElementsData acquisition (DAQ)
analogue to digital converter (ADC)
Computation circuit boardDisplayBatteryCase
Specific Details of Chosen Design
Laser sourceQL7816S-B-L785 nm, 25 mW, Ø5.6 mm, B
Pin Code Laser DiodeThe laser diode provides a
single wavelength light sourceA single wavelength light
source is preferable to a source of a broad range of wavelengths
As the spectral peaks of glucose and hemoglobin are relative to wavelength of the simulation laser, broader simulation sources will result in broader spectral peaks.
Collimating LensLT220P-BCollimation Tube with Optic for
Ø5.6 and Ø9 mm Laser Diodes, f = 11.0 mm
Converts the diverging light from the laser diode to parallel laser light, needed to progress through preceding optical elements
The main consideration of the collimation tube is the width of output collimated light
A width too narrow is prone to optical misalignment whereas a width too wide increases the sizes of optical elements requires
Beam splittersBS01150:50 Non-Polarizing
Beamsplitter Cube, 700-1100 nm, 10 mm
The main considerations for the beam splitters is the ratio of light intensity between the split. This ratio determines how much of the incoming light will be transmitted through the cube versus deflected 90 degrees.
Objective (focusing) lensC240TME-B f = 8.0 mm, NA = 0.5,
Mounted Geltech Aspheric Lens, AR: 600-1050 nm
The objective lens is used to focus the collimated laser light to a focused spot in the skin, and to capture and collimate the backscattered Raman signal.
The lens must also focus the laser light to a point on a blood vessel near the surface of the skin, as the optical penetration depth at 785 nm is around 1 mm in tissue.
Bandpass filtersHemoglobin Bandpass
filter: FB890-10Ø1in Bandpass Filter,
CWL = 890 ± 2 nm, FWHM = 10 ± 2 nm
Glucose bandpass filter: FB860-10
Ø1in Bandpass Filter, CWL = 860 ± 2 nm, FWHM = 10 ± 2 nm
PhotodetectorsFDS100Si Photodiode, 10 ns Rise
Time, 350 - 1100 nm, 3.6 mm x 3.6 mm Active Area
The photodetector outputs a current indicative of measured light intensity.
Two photodetectors are used in the device: one to measure the intensity of the glucose peak, the other to measure the intensity of the hemoglobin peak.
Updated Design Schedule
Updated Team ResponsibilitiesNelson Wu
Contact for ClientWebsite ModeratorKnowledge on alternative spectroscopies
Cong ZhangKnowledge on Optical ComponentsKnowledge on Raman Spectroscopy
Tom ZhouKnowledge on Non-Optical ComponentsProgrammer
Questions?
References 1. Kong et al. “Clinical Feasibility of Raman Spectroscopy for Quantitative Blood Glucose Measurement.”
Massachusetts Institute of Technology. 2011. 2. Larin, K. V., M. S. Eledrisi, M. Motamedi, and R. O. Esenaliev. "Noninvasive Blood Glucose Monitoring With Optical
Coherence Tomography: A Pilot Study In Human Subjects ." Diabetes Care 25.12 (2002): 2263-2267. Print. 3. N.D. Evans, L. Gnudi, O. J. Rolinski, D. J. S. Birch, and J. C. Pickup. “Non-invasive glucose monitoring by NAD(P)H
Autofluorescence spectroscopy in broblasts and adipocytes:a model for skin glucose sensing.” Diabetes Technology and Therapeutics 5 (2003): 807-816. Print.
4. Pishko, Michael V.. "Analysis: Glucose Monitoring By Reverse Iontophoresis." Diabetes Technology Therapeutics 2.2 (2000): 209-210. Print.
5. Plaitez, Miguel, Tobias Leiblein, and Alexander Bauer. "In Vivo Noninvasive Monitoring of Glucose Concentration in Human Epidermis by Mid-Infrared Pulsed Photoacoustic Spectroscopy." Analytical Chemistry 85.2 (2013): 1013-1020. Print.
6. Potts, Russel, Janet Tamada, and Micheal Tearny. "Glucose monitoring by reverse iontophoresis." Diabetes/metabolism research and reviews 18 (2002): 49-53. Print.
7. Shao et al. “In Vivo Blood Glucose Quantification Using Raman Spectroscopy.” Fuzhou University. 2012. 8. Thenadil, Suresh, and Jessica Rennert. "Comparison of Glucose Concentration in Interstitial Fluid, and Capillary and
Venous Blood During Rapid Changes in Blood Glucose Levels." Diabetes Technology & Therapeutics 3.3 (2004): 357-365. Print.
9. Whiting, D., Weil, C., & Shaw, J. (2011). IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Research and Clinical Practice, 94(3), 311-321.
10. Vashist, Sandeep. "Non-invasive glucose monitoring technology in diabetes management: A review." Analytica Chimica Acta 750 (2012): 16-27. Print.
11. Yang, Chaoshin, Chiawei Chang, and Jenshinn Lin. "A Comparison between Venous and Finger-Prick Blood Sampling on Values of Blood Glucose." International Conference on Nutrition and Food Sciences 39 (2012): 207-210. Print.
12. Zhang, Ping, Xinzhi Zhang, and Jonathan Brown. "Global healthcare expenditure on diabetes for 2010 and 2030." Diabetes Research and Clinical Practice 87.3 (2010): 293-301. Print.